# stringr
Strings are not glamorous, high-profile components of R, but they do
play a big role in many data cleaning and preparations tasks. R
provides a solid set of string operations, but because they have grown
organically over time, they can be inconsistent and a little hard to
learn. Additionally, they lag behind the string operations in other
programming languages, so that some things that are easy to do in
languages like Ruby or Python are rather hard to do in R. The
`stringr` package aims to remedy these problems by providing a clean,
modern interface to common string operations.
More concretely, `stringr`:
* Processes factors and characters in the same way.
* Gives functions consistent names and arguments.
* Simplifies string operations by eliminating options that you don't
need 95% of the time.
* Produces outputs than can easily be used as inputs. This includes
ensuring that missing inputs result in missing outputs, and zero
length inputs result in zero length outputs.
* Completes R's string handling functions with useful functions from
other programming languages.
stringr 0.6
===========
* new modifier `perl` that switches to Perl regular expressions
* `str_match` now uses new base function `regmatches` to extract matches -
this should hopefully be faster than my previous pure R algorithm
--
Assistant Professor / Dobelman Family Junior Chair
Department of Statistics / Rice University
http://had.co.nz/